Content Analysis

Analogue

• Printed copies of the material
• Highlighters
• Moderation cards
• Pinboard

Digital

• Spreadsheet software
• Document editing software
• Analysis software (optional)
• Digital whiteboard

Collect all material that will be analysed.

For example:

• interview transcripts
• workshop minutes
• survey responses
• written statements
• documentation
• photographs or videos

Clarify which question the analysis should answer.

Examples:

• Which topics are mentioned most frequently?
• Which needs become visible?
• What differences exist between different target groups?
• Which measures are preferred?

The different approaches to content analysis can be combined. In many cases, themes are first developed inductively and then examined further using comparative or contextual analysis.

Combining different approaches makes the method easier to understand and helps users select the most appropriate type of analysis for their specific use case.

The following approaches are available:

Qualitative Content Analysis systematically examines statements, texts, or conversations to identify meanings, opinions, needs, and patterns of argumentation.

The material is assigned to categories and then interpreted. The focus is not primarily on how often something is mentioned, but rather what is being said and what it means.

Example

In interviews about urban development, participants state:

• "I don't feel safe at night."
• "There aren't enough well-lit pathways."
• "The park feels uncomfortable after dark."

These statements can be assigned to the category Safety and interpreted together.

Suitable when...

• needs and perspectives should be understood.
• interviews or open-ended survey responses are being analysed.
• motivations and underlying reasons should be explored.
• the goal is to understand why people think or behave in a certain way.

Not suitable when...

• only numerical results or frequencies are required.
• very large datasets need to be analysed quickly.

In deductive Content Analysis, categories are established before the analysis begins.

The analysis then examines which statements fit these predefined categories.

The process moves from theory or research questions to the data.

Example

A municipality wants to evaluate perceptions of a mobility concept.

The following categories are defined beforehand:

• Safety
• Quality of public spaces
• Accessibility
• Barrier-free access

All statements are then assigned to these categories.

Suitable when...

• a clearly defined research question needs to be answered.
• existing goals, criteria, or concepts are being evaluated.
• results from different projects should be compared.
• a structured and comparable analysis is required.

Not suitable when...

• the aim is to discover which topics are relevant.
• unexpected findings are being sought.

In inductive Content Analysis, categories are not defined in advance.

Instead, they emerge directly from the material during the analysis.

The process moves from the data towards theory.

Example

Interviews with residents repeatedly mention:

• lack of meeting places
• insufficient seating
• poor lighting
• inadequate orientation

These recurring issues gradually develop into categories.

Suitable when...

• an open and exploratory analysis is desired.
• little prior knowledge about the topic exists.
• new themes and perspectives should be discovered.

Not suitable when...

• clear evaluation criteria already exist.
• results must be directly comparable with previous studies.

This approach compares different groups, points in time, or datasets.

The central question is: Who says what, and where are the similarities and differences?

Example

A municipality compares feedback on the same public square from:

• young people
• older adults
• local business owners

The analysis shows:

• Young people want more places to gather.
• Older adults want additional seating.
• Business owners want more parking spaces.

Suitable when...

• different target groups should be compared.
• common ground and conflicts should be identified.
• differences in needs between groups should be examined.
• changes over time should be analysed.

Not suitable when...

• only one dataset or one target group is available.
• there is no comparative research question.

In Contextual Content Analysis, statements are not interpreted in isolation but always in relation to the context in which they were made.

Possible contextual factors include:

• spatial conditions
• social circumstances
• political frameworks
• cultural backgrounds
• historical developments

The guiding question is:

Why is this being said, and in what context does this statement arise?

Example

Residents in two different neighbourhoods report feeling unsafe.

The analysis reveals:

• Neighbourhood A: poor street lighting
• Neighbourhood B: lack of social surveillance and vacant buildings

Although both groups mention the same issue—safety—the underlying causes are different.

Suitable when...

• complex relationships need to be understood.
• spatial or societal factors should be taken into account.
• supporting urban planning or community development projects.
• the aim is to understand underlying causes rather than only symptoms.

Not suitable when...

• only a quick overview or a list of priorities is required.
• little background information is available.

First, read through all of the collected material carefully.

While reviewing the material, highlight:

• important statements
• recurring terms
• notable observations
• interesting examples

Assign statements to appropriate categories.

Example:

• "The cycle path is too narrow." → Cycling Infrastructure
• "The intersection feels dangerous." → Safety
• "There aren't enough seating areas." → Quality of Public Space

A single statement may be assigned to more than one category.

Systematically work through all of the material.

Assign every relevant statement to one or more appropriate categories. This creates a structured overview of the collected information.

Analyse the categorised data by asking:

• Which themes occur most frequently?
• Which themes tend to appear together?
• What differences can be identified between groups?
• Which statements contradict one another?

Discuss the meaning of the findings.

Helpful questions include:

• What do these results tell us about the situation?
• Which needs become visible?
• What actions appear to be necessary?
• Which topics should be explored further?

Condense the results into key findings.

Example:

Many participants identified safety issues in public streets. The most frequently mentioned concerns were confusing intersections and a lack of safe crossing points.

The documentation should include:

• the categories used
• key findings
• frequencies
• representative quotes or examples
• recommendations for action

Suitable formats include:

• tables
• charts
• infographics
• thematic clusters
• maps

The findings can provide a basis for:

• developing measures and actions
• setting priorities
• political or administrative decision-making
• further participation processes

Source: Kerr, J., Cheers, J., Gallegos, D., Blackler, A. & Kelly, N. (2023): The Art of Co-Design: A Guide Through Creative Collaboration. BIS Publishers.